{"id":"W4225763513","doi":"10.1177/00220345211072484","title":"Nanomechanical and Molecular Characterization of Aging in Dentinal Collagen","year":2022,"lang":"en","type":"article","venue":"Journal of Dental Research","topic":"Dental materials and restorations","field":"Dentistry","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico","keywords":"Dentin; Demineralization; Dentinal Tubule; Nanoindentation; Chemistry; Ultrastructure; Crown (dentistry); Glycation; Dentinogenesis; Collagen fibril; Matrix (chemical analysis); Pulp (tooth); Fibril; Biophysics; Dentistry; Anatomy; Materials science; Composite material; Biochemistry; Odontoblast; Biology; Enamel paint; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001730496,0.0001378029,0.00006852839,0.0003989612,0.0001035758,0.0001079332,0.00007473945,0.000156435,0.0004346377],"category_scores_gemma":[0.0001687644,0.00009799908,0.0001135056,0.0002203425,0.0001283415,0.0001426945,0.0001001945,0.0001250744,0.00009053481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006395605,"about_ca_system_score_gemma":0.00006718303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007285685,"about_ca_topic_score_gemma":0.0009796536,"domain_scores_codex":[0.9999341,0.00001009022,0.000006223921,0.00001782246,0.00002012906,0.00001166014],"domain_scores_gemma":[0.9998351,0.00002783085,0.00005633793,0.00001177432,0.00004596585,0.00002282245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005039697,0.000005631673,0.00382895,0.00003346836,0.000005011049,0.00004695714,0.00003485035,0.00002938065,0.994555,0.00001499106,0.000007543676,0.001387859],"study_design_scores_gemma":[0.000008298974,0.0004217415,0.4661687,0.00001570672,0.00005181109,0.001217496,0.000327452,0.001807909,0.5277457,0.00008255451,0.002138367,0.00001430899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950637,0.001597144,0.002801559,0.00001474056,0.000009009315,0.00001126995,0.0002037841,0.000007538385,0.0002911988],"genre_scores_gemma":[0.9925011,0.001175021,0.005073973,0.00003277409,0.00001113683,0.0000267947,0.0002994839,0.000005476802,0.0008743968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007285685,"threshold_uncertainty_score":0.001453996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04010726448409752,"score_gpt":0.368644026600952,"score_spread":0.3285367621168545,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}